Machine learning can be used to automatically identify objects depicted in images. Machine learning systems can use neural networks to analyze the images for a variety of purposes, such as to automatically identify distress (e.g., damage) to machines. For example, cracks, spalling, pits, etc. in turbine blades or coatings on turbine blades of a turbine machine can be automatically identified by inserting a borescope into the turbine machine and obtaining images of the turbine blades.
But, differentiating the turbine blades from each other can be difficult. Because the turbine blades are so similar in appearance, it can be difficult to track changes in damage to a particular turbine blade over time. The operator of the borescope and the machine learning system may not be aware of which turbine blade is being imaged due to the rotational symmetry of turbine machines. While the turbine machine can be disassembled to differentiate the turbine blades from each other, the disassembly is a time consuming and costly endeavor.